Show simple item record

dc.contributor.authorLopez, Yosvany
dc.contributor.authorSharma, Alok
dc.contributor.authorDehzangi, Abdollah
dc.contributor.authorLal, Sunil Pranit
dc.contributor.authorTaherzadeh, Ghazaleh
dc.contributor.authorSattar, Abdul
dc.contributor.authorTsunoda, Tatsuhiko
dc.date.accessioned2019-06-26T12:31:22Z
dc.date.available2019-06-26T12:31:22Z
dc.date.issued2018
dc.identifier.issn1471-2164
dc.identifier.doi10.1186/s12864-017-4336-8
dc.identifier.urihttp://hdl.handle.net/10072/379884
dc.description.abstractBackground: Post-translational modification is considered an important biological mechanism with critical impact on the diversification of the proteome. Although a long list of such modifications has been studied, succinylation of lysine residues has recently attracted the interest of the scientific community. The experimental detection of succinylation sites is an expensive process, which consumes a lot of time and resources. Therefore, computational predictors of this covalent modification have emerged as a last resort to tackling lysine succinylation. Results: In this paper, we propose a novel computational predictor called ‘Success’, which efficiently uses the structural and evolutionary information of amino acids for predicting succinylation sites. To do this, each lysine was described as a vector that combined the above information of surrounding amino acids. We then designed a support vector machine with a radial basis function kernel for discriminating between succinylated and non-succinylated residues. We finally compared the Success predictor with three state-of-the-art predictors in the literature. As a result, our proposed predictor showed a significant improvement over the compared predictors in statistical metrics, such as sensitivity (0.866), accuracy (0.838) and Matthews correlation coefficient (0.677) on a benchmark dataset. Conclusions: The proposed predictor effectively uses the structural and evolutionary information of the amino acids surrounding a lysine. The bigram feature extraction approach, while retaining the same number of features, facilitates a better description of lysines. A support vector machine with a radial basis function kernel was used to discriminate between modified and unmodified lysines. The aforementioned aspects make the Success predictor outperform three state-of-the-art predictors in succinylation detection.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherBioMed Central
dc.publisher.placeUnited Kingdom
dc.relation.ispartofchapter923
dc.relation.ispartofpagefrom1
dc.relation.ispartofpageto10
dc.relation.ispartofjournalBMC Genomics
dc.relation.ispartofvolume19
dc.subject.fieldofresearchBiological sciences
dc.subject.fieldofresearchBiomedical and clinical sciences
dc.subject.fieldofresearchcode31
dc.subject.fieldofresearchcode32
dc.titleSuccess: evolutionary and structural properties of amino acids prove effective for succinylation site prediction
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
gro.hasfulltextFull Text
gro.griffith.authorSattar, Abdul
gro.griffith.authorSharma, Alok
gro.griffith.authorTaherzadeh, Ghazaleh


Files in this item

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record